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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.6 No.2
- 발행연도
- 2017.4
- 수록면
- 85 - 92 (8page)
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초록· 키워드
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This paper presents a dehazing method based on a fuzzy membership function and variational method. The proposed algorithm consists of three steps: i) estimate transmission through a pixel-based operation using a fuzzy membership function, ii) refine the transmission using an L1- norm–based regularization method, and iii) obtain the result of haze removal based on a hazy image formation model using the refined transmission. In order to prevent color distortion of the sky region seen in conventional methods, we use a trapezoid-type fuzzy membership function. The proposed method acquires high-quality images without halo artifacts and loss of color contrast.
목차
Abstract
1. Introduction
2. Haze Model
3. Estimate Transmission using Fuzzy Membership Function
4. Refine the Transmission using the Variational Method
5. Experimental Result
6. Conclusion
References
참고문헌 (36)
참고문헌 신청
S. Narasimhan and S. Nayar, “ Vision and the 48, no. 3, pp. 233-254, July 2002. Article (CrossRefLink)
S. Narasimhan and S. Nayar, “Contrast restoration of weather degraded images, ” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 713-724, June 2003. Article (CrossRefLink)
S. Shwartz, E. namer, and Y. Schecher, “Blind haze separation,” Proc. IEEE Int. Conf. Computer Vision, Pattern Recognition, pp. 1984-1991, October 2006. Article (CrossRefLink)
Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “ Instant dehazing of images using polarization, ” Proc. IEEE Int. Conf. Computer Vision, Pattern Recognition, pp. 325-332, Dec. 2001. Article (CrossRefLink)
R. Tan, “ Visibility in bad weather from a single image,” IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, June 2008. Article (CrossRefLink)
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